This document provides an overview of qualitative data analysis, highlighting its purpose in discovering underlying meanings and patterns through non-numerical examination. It discusses the interplay between theory and analysis, methods such as grounded theory, semiotics, and conversation analysis, and the importance of data processing tools like coding, memoing, and concept mapping. Additionally, it mentions the use of software programs designed for qualitative data analysis.

1. ©2011, Brooks/Cole Publishing, A
Division of Cengage Learning, Inc.
Chapter 20
Qualitative Data Analysis
PowerPoint presentation developed by:
Jennifer Manuel & Sarah E. Bledsoe

2. ©2011, Brooks/Cole Publishing, A
Division of Cengage Learning, Inc.
Overview
Introduction
Linking Theory and Analysis
Qualitative Data Processing
Computer Programs for Qualitative Data

3. ©2011, Brooks/Cole Publishing, A
Division of Cengage Learning, Inc.
Introduction
Qualitative analysis is the nonnumerical
examination and interpretation of
observations
– Purpose is to discover underlying meanings
and patterns, such as changes over time or
possible causal links between variables
– Involves a continuing interplay between data
collection and theory

4. ©2011, Brooks/Cole Publishing, A
Division of Cengage Learning, Inc.
Linking Theory and Analysis
Theories represent our understanding of how
life operates
The more our research confirms a set of
relationships among a set of concepts, the
more confident we become that our
understanding coincides with reality

5. ©2011, Brooks/Cole Publishing, A
Division of Cengage Learning, Inc.
Linking Theory and Analysis
In examining your data, you will look for patterns
– Variable-oriented analysis attempts to gain a partial,
overall explanation by focusing on the interrelations
among a small number of variables (e.g., voting intentions
based on two or three key variables)
– Case-oriented analysis attempts to understand a
particular case fully (e.g., voting intentions based on as
many factors as possible in one case)
– Cross-case analysis involves the researcher paying close
attention to the variables important in the first case while
also understanding other cases in full detail and to explore
why cases reflect similar or different patterns

6. ©2011, Brooks/Cole Publishing, A
Division of Cengage Learning, Inc.
Formal Qualitative Analysis Methods
Grounded Theory Method
– Fundamental, inductive tenet of building theory
from data
– Employs constant comparative method, which
involves 4 stages:
• Comparing evidence of concepts across cases
• Combining concepts and their phenomena
• Restricting concepts
• Reporting theory

7. ©2011, Brooks/Cole Publishing, A
Division of Cengage Learning, Inc.
Formal Qualitative Analysis Methods
Semiotics
– “Science of signs”, involving the search for meanings
intentionally or unintentionally attached to signs
– The meanings we “know” today are socially constructed
– E.g., link the signs below with their meanings:
Sign Meaning
1. Poinsettia
2. Horseshoe
3. Blue ribbon
4. “Say cheese”
5. “Break a leg”
a. Good luck
b. First prize
c. Christmas
d. Acting
e. Smile for a picture

8. ©2011, Brooks/Cole Publishing, A
Division of Cengage Learning, Inc.
Formal Qualitative Analysis Methods
Conversation Analysis
– Seeks to uncover the implicit assumptions and
structures in social life through a close scrutiny of
the way we converse with each other
– 3 fundamental assumptions:
• Conversation is a socially structured activity
• Conversations must be understood in context
• Conversation analysis attempts to understand the
structure and meaning of conversations through exact
transcripts of conversations (i.e., exact words, uhs, ers,
pauses and bad grammar are all noted)

9. ©2011, Brooks/Cole Publishing, A
Division of Cengage Learning, Inc.
Qualitative Data Processing
The processing of qualitative data is as much
art as science
Three key tools for preparing data for analysis
are
– Coding
– Memoing
– Concept mapping

10. ©2011, Brooks/Cole Publishing, A
Division of Cengage Learning, Inc.
Qualitative Data Processing: Coding
Coding involves classifying or categorizing
individual pieces of data coupled with some
kind of retrieval system
The concept is the organizing principle for
qualitative coding
Hypothesis-driven coding versus open coding
– Hypothesis-driven coding involves generating
codes based on theory a priori
– Open coding pertains to categorizing information
through close examination and questioning of the
data

11. ©2011, Brooks/Cole Publishing, A
Division of Cengage Learning, Inc.
Qualitative Data Processing: Memoing
Memoing involves writing memos or notes to
yourself or others involved in the project
during analysis
Captures code meanings, theoretical ideas,
preliminary conclusions, and other thoughts
that will be useful during analysis, as well as in
writing up the results
3 types of memos: code notes, theoretical
notes, and operational notes

12. ©2011, Brooks/Cole Publishing, A
Division of Cengage Learning, Inc.
Qualitative Data Processing: Concept
Mapping
Concept mapping uses diagrams to explore relationships
in the data graphically
An example of concept mapping (Fig. 19-3)
Active/passive
rolesPhysical
Location
Social Status Gender
Power Authority Servant/ Master
Social Worth

13. ©2011, Brooks/Cole Publishing, A
Division of Cengage Learning, Inc.
Computer Programs for Qualitative
Data
Researchers can take advantage of the
capabilities of common software tools such as
word processors, database programs, and
spreadsheets
Several computer programs, such as NUD*IST,
are specifically designed to assist researchers in
the analysis of qualitative data
Sociologists at the University of Surrey, England
have prepared a list of programs:
www.soc.surrey.ac.uk/sru/SRU1.html